A canonical theory of dynamic decision-making

Decision-making behavior is studied in many very different fields, from medicine and eco- nomics to psychology and neuroscience, with major contributions from mathematics and statistics, computer science, AI, and other technical disciplines. However the conceptual- ization of what decision-making is and methods for studying it vary greatly and this has resulted in fragmentation of the field. A theory that can accommodate various perspectives may facilitate interdisciplinary working. We present such a theory in which decision-making is articulated as a set of canonical functions that are sufficiently general to accommodate diverse viewpoints, yet sufficiently precise that they can be instantiated in different ways for specific theoretical or practical purposes. The canons cover the whole decision cycle, from the framing of a decision based on the goals, beliefs, and background knowledge of the decision-maker to the formulation of decision options, establishing preferences over them, and making commitments. Commitments can lead to the initiation of new decisions and any step in the cycle can incorporate reasoning about previous decisions and the rationales for them, and lead to revising or abandoning existing commitments. The theory situates decision-making with respect to other high-level cognitive capabilities like problem solving, planning, and collaborative decision-making. The canonical approach is assessed in three domains: cognitive and neuropsychology, artificial intelligence, and decision engineering

The Evidence of the Senses: A Predictive Processing-Based Take on the Sellarsian Dilemma

Traditional foundationalist empiricist projects in epistemology postulated that sensory states of the subject are epistemically basic, in that they are capable of conferring justification on mental representations of the world without themselves needing to be (inferentially) justified by any antecedent representational states. This sort of view faces a seemingly hopeless dilemma, whose recognition is usually attributed to Wilfrid Sellars. If we treat sensory states as brute stimulations devoid of intentional content, then it is hard to see how the senses could provide subjects with anything that could possibly feature in justification-conferring relations with representational states. If we treat them as contentful, then in order to justify contentful states, sensory states themselves would presumably need to be justified by other representational states; but if this is so, they are not able to play a properly foundational epistemic role. In the article, I use the Predictive Processing (PP) view of perception in order to sketch a possible resolution of the Sellarsian dilemma. I draw on PP in order to show how sensory states could actually serve a normative role that is recognizably similar to the one envisioned by traditional empiricists. To do this, I first distinguish representational from non-representational posits of PP and subsequently focus on the role that PP ascribes to sensory or “driving” signal. In particular, I argue that (1) the driving signal plays a role of a non-representational, contentless detector; at the same time, (2) it serves as an “impartial” or “theory-neutral” tribunal against which contentful internal models are actively tested and updated. Drawing on Anil Gupta’s work, I discuss the epistemic involvement of the sensory signal in perceptual inference and show how the signal provides conditional justification (i.e. justification that is conditional on the justification or rationality of prior knowledge) to perceptual hypotheses. Then I discuss the role the sensory signal plays in perceptual learning. I employ the notion of “epistemic convergence” to sketch out how the sensory signal could provide perceivers with unconditional justification (i.e. one that is not relativized to the justification of prior knowledge). If this approach is right, the Sellarsian dilemma seems to be averted. We can see how the senses can be at the same time silent (i.e. contentless) and capable of playing a sort of foundational epistemic role

Policy learning and diffusion of Tokyo's metropolitan cap-and-trade: making a mandatory reduction of total CO2 emissions work at local scales

The process of adopting policy ideas is extremely complex and requires a close examination of the political context in which the idea is learned, articulated, contested, adapted, and accepted by agents, both individual and collective. Why and how was the world's first urban scheme of mandatory reduction of total emissions adopted in Tokyo and not elsewhere? What might cause diffusion of this idea in other urban areas? One key explanation behind the idea adoption is a policy evolution of trial-and-error lessons about effective policy design, desirable policy goals, and politically feasible judgments. This study finds that both agency effects and structural opportunities of policy adoption in the case of Tokyo's cap-and-trade are too specific to result in a more coherent diffusion of ideas, policies, and practices in other urban areas. Although there is a sign of diffusion of Tokyo's cap-and-trade throughout Japan, it is more likely to derive from mimicking behaviors than from learning. The policy transfer of Tokyo's cap-and-trade requires the continuous learning of adaptive capacity to make it better fit to locally specific conditions

An introduction to predictive processing models of perception and decision-making

The predictive processing framework includes a broad set of ideas, which might be articulated and developed in a variety of ways, concerning how the brain may leverage predictive models when implementing perception, cognition, decision-making, and motor control. This article provides an up-to-date introduction to the two most influential theories within this framework: predictive coding and active inference. The first half of the paper (Sections 2–5) reviews the evolution of predictive coding, from early ideas about efficient coding in the visual system to a more general model encompassing perception, cognition, and motor control. The theory is characterized in terms of the claims it makes at Marr's computational, algorithmic, and implementation levels of description, and the conceptual and mathematical connections between predictive coding, Bayesian inference, and variational free energy (a quantity jointly evaluating model accuracy and complexity) are explored. The second half of the paper (Sections 6–8) turns to recent theories of active inference. Like predictive coding, active inference models assume that perceptual and learning processes minimize variational free energy as a means of approximating Bayesian inference in a biologically plausible manner. However, these models focus primarily on planning and decision-making processes that predictive coding models were not developed to address. Under active inference, an agent evaluates potential plans (action sequences) based on their expected free energy (a quantity that combines anticipated reward and information gain). The agent is assumed to represent the world as a partially observable Markov decision process with discrete time and discrete states. Current research applications of active inference models are described, including a range of simulation work, as well as studies fitting models to empirical data. The paper concludes by considering future research directions that will be important for further development of both models

Missed Expectations: The Argentine Convertibility

This paper studies the process that led to the Argentine crisis. The crisis is understood as a major disappointment of previous expectations, indicated by widespread insolvencies and abrupt declines in consumption. The analysis concentrates on the sequence of public and private decisions, and the varying perceptions and policy incentives that motivated them. In the nineties Argentina searched for a new growth trend. During much of the period, the behavior of agents seemed to be based on the anticipation that current and future incomes could sustain a value of domestic spending much higher than in the past. The government was motivated to reinforce those expectations, for signaling and political economy reasons. The convertibility monetary regime not only provided a very visible nominal anchor, but also operated as a basic framework for financial contracts, mostly denominated in dollars. Dollar contracting implicitly presumed that the dollar value of incomes would support the servicing of debts. Despite precautionary measures, the reliance on the sustainability of the real exchange rate increased over time. In the late nineties exports stopped rising and the foreign supply of credit tightened. Facing these contraints, the economy contracted and the solvency of the government was put into question. The financial system was vulnerable both in the event of devaluation and that of a (large) deflation-cum-adjustment. As was implicit in its design and management, convertibility proved to have very large exit costs.http://deepblue.lib.umich.edu/bitstream/2027.42/39900/3/wp515.pd

Joining the dots: hydrology, freshwater ecosystem values and adaptation options

AbstractThe objective of this research was to investigate and test the necessary steps in developing an adaptation planning framework for freshwater biodiversity. We used Tasmania as a test case to demonstrate how downscaled climate model outputs could be integrated with spatially resolved hydrological models and freshwater biodiversity data. This enabled us to scope adaptation actions at local, regional and state scales for Tasmania, and to explore how priorities might be set.To achieve this integration we quantified how different climate change scenarios could affect the risks to biodiversity and ecosystem values (‘biodiversity assets’) in freshwaters, the scope and types of adaptation actions, and assessed the strengths and weaknesses of the policy and planning instruments in responding to climate change.We concluded that downscaled climate modelling, linked with modelling of catchment and hydrological processes, refines projections for climate-driven risks to aquatic environments. Spatial and temporal hazards and risks can now be compared at a variety of scales, as well as comparisons between biodiversity assets (e.g. relative risk to riparian vegetation v. in-stream biota). Uncertainties can be identified and built into adaptation processes. Notwithstanding this progress, we identified a number of issues that need to be addressed in order to increase confidence in this process.The main issues for improved and timely modelling are: frameworks for using and downscaling outputs from improved global climate models as they become available; better data on thermal tolerances of freshwater biota; and, improved methods for predicting key water temperature variables from air temperature and other biophysical predictors. Improvements are also needed in updating and maintaining high quality biodiversity data sets, and better spatially explicit information on the contributions of groundwater to surface waters and rates of recharge.The list of adaptation options available is extensive, but the key challenge is to organise these options so that stakeholders are not overwhelmed. Scenario modelling that incorporates explicit tools for comparing costs, benefits, feasibility and social acceptability should help with setting priorities but require further development.A review of current Australian policies revealed a variety of responses driven by both water reform and climate change agendas. Many agencies are actively revising their policies to accommodate adaptation. However, we note that much of the reform of the water sector in the last 10–15 years has aimed to improve certainty for non-environmental water uses. Under the National Water Initiative, governments have agreed that entitlement holders should bear the risks of reduced volumes or reliability of their water allocations as a result of changes in climate. The key opportunity for adaptive uptake of climate adaptations is by developing and periodically reviewing water management planning tools. Pathways need to be developed for integrating the traditional evolution of planning and policy with the needs for climate change adaptation for aquatic ecosystems. Formal mechanisms for the uptake of knowledge about identified risks into policy and legislative instruments remain under-developed. An even bigger challenge is to integrate multiple adaptation strategies (sometimes at different scales) to achieve specific adaptation objectives within regions or catchments—especially where a mix of water management and non-water management is required

Missed Expectations: The Argentine Convertibility

This paper studies the process that led to the Argentine crisis. The crisis is understood as a major disappointment of previous expectations, indicated by widespread insolvencies and abrupt declines in consumption. The analysis concentrates on the sequence of public and private decisions, and the varying perceptions and policy incentives that motivated them. In the nineties Argentina searched for a new growth trend. During much of the period, the behavior of agents seemed to be based on the anticipation that current and future incomes could sustain a value of domestic spending much higher than in the past. The government was motivated to reinforce those expectations, for signaling and political economy reasons. The convertibility monetary regime not only provided a very visible nominal anchor, but also operated as a basic framework for financial contracts, mostly denominated in dollars. Dollar contracting implicitly presumed that the dollar value of incomes would support the servicing of debts. Despite precautionary measures, the reliance on the sustainability of the real exchange rate increased over time. In the late nineties exports stopped rising and the foreign supply of credit tightened. Facing these contraints, the economy contracted and the solvency of the government was put into question. The financial system was vulnerable both in the event of devaluation and that of a (large) deflation-cum-adjustment. As was implicit in its design and management, convertibility proved to have very large exit costs.Economic Crisis, Contracts, Convertibility and Wealth Perceptions

Open-mindedness and Deliberative Democracy

The dominant justificatory framework for democracy is deliberative democratic theory. It holds that democracy is legitimate to the extent it instantiates, and is guided by, the ideals and processes of good deliberation. This thesis challenges the dominance of the deliberative paradigm by highlighting an under-explored, and yet critical, element of the theory – its dependence on participants’ open-mindedness. The thesis addresses two central issues – the empirical feasibility and normative desirability of open-mindedness. By surveying the psychological literature on directionally motivated reasoning this thesis identifies robust findings across a range of contexts and subjects that people engaged with, or knowledgeable about, politics are systematically closed-minded in a manner resistant to straightforward correction. This analysis is twinned with a novel methodological approach to feasibility. This entails that if we are to maintain any connection to ‘ought implies can’ we cannot draw any firm dividing line in feasibility analysis between impossibility and the types of probabilistic discoveries produced by the social sciences, such as motivated reasoning. Therefore such results have to be accounted for in normative theorising. This thesis builds a novel account of open-mindedness and its related phenomena – credulity and closed-mindedness – and finds that whether one ought to be open-minded is sensitive to a range of contextual criteria. It applies this context-sensitive approach to the case of elected representatives as centrally important figures in modern democracies. In particular, the practice of elections and electoral campaigning require elected representatives to uphold their electoral commitments while in office, an obligation put at risk by open-mindedness. The adversarial political context faced by elected representatives and their limited internal capabilities provides further reasons to deviate from open-mindedness. These findings call into question the central role open-mindedness plays in deliberative democratic theory. As a result, they open up theoretical space to explore alternative justifications for democracy’s legitimacy